Engineered nanoparticles are moving toward clinical use as drug delivery, imaging and therapeutic agents. Side effects of nanoparticle interactions with cells, and occasionally organisms, are studied (e.g., toxicity) but the measured outputs are usually blunt (e.g., live/dead assays) and provide little insight into the nanoparticle chemistry and mechanisms that trigger inflammation and tissue damage. Moreover, many in vitro tests are based on acute nanoparticle exposure to cell monocultures, whereas effects on tissue physiology may only appear after chronic exposure. An alternative is to use animal models, but the outcomes of such studies have not provided sufficient mechanistic insight to justify the expense and ethical challenges of extensive animal testing. Increasingly sophisticated cell culture experiments allow for better prediction of in vivo responses to agents. The most likely point of entry of nanoparticulates to humans is the lung. Beyond the use of primary cell cultures, adding mechanical stretch, an air-water interface, and fluid flow to standard cell conditions far better approximates the physiological environment within the lung. In addition, dynamic imaging capabilities with protein-based fluorescent reporters enable the real time monitoring of signaling and altered tissue phenotype in situ, without the need for fixation. The goal of this work is to combine these advances to measure the response of pulmonary cell arrays to a suite of nanoparticles of well-defined size, shape, and surface chemistry upon mechanical stretch and flow conditions for both acute and chronic time scales. Disease progression (inflammation) will be monitored on chip, by focusing on inflammatory signatures including reactive oxygen species and cytokine production, cytoskeletal remodeling, and compromised intercellular barrier integrity. The surface chemistry of the nanoparticles will be modified to be anti-biofouling, to tet the hypothesis that surface chemical modification of nanoparticles can mitigate adverse impacts. Overall, this methodology might lead to more realistic organ-on-a-chip models without the use of animals to predict emerging contaminant impact.